Critical functionalities of a successful e-learning system - An analysis from instructors' cognitive structure toward system usage

Decision Support Systems

Volumn 48, Issue 1, 2009, Pages 293-302

  Sun, Pei chen ^a   Cheng, Hsing Kenneth ^b   Finger, Glenn ^c  

^a NATIONAL KAOHSIUNG NORMAL UNIVERSITY   (Taiwan)

^b UNIVERSITY OF FLORIDA   (United States)

^c GRIFFITH UNIVERSITY   (Australia)

Author keywords

Critical functionalities; E learning system; Means end chain; Requirement analysis

Indexed keywords

COGNITIVE STRUCTURES; CRITICAL FUNCTIONALITIES; FUNCTIONAL REQUIREMENT; MEANS-END CHAIN; ONLINE FORUMS; REQUIREMENT ANALYSIS; STUDENT LEARNING; THREADED DISCUSSIONS; TWO-DIMENSION; WHITE BOARD;

INFORMATION SYSTEMS; MULTIMEDIA SYSTEMS; RESEARCH; STUDENTS;

E-LEARNING;

EID: 70350570474     PISSN: 01679236     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.dss.2009.08.007     Document Type: Article

References (39)

1. Ainsworth S., and Fleming P. Evaluating authoring tools for instructors as instructional designers. Computers in Human Behavior 22 (2006) 131-148
2. Aschmoneit P., and Heitmann M. Consumers Cognition towards Communities: Customer-Centred Community Design Using the Means-End Chain Perspective (2003), The Hawaii International Conference on System Sciences, Big Island, Hawaii
3. Chou C. Interactivity and interactive functionalities in web-based learning systems: a technical framework for designers. British Journal of Educational Technology 34 3 (2003) 265-279
4. Chiu C.M. Applying means-end chain theory to eliciting system requirements and understanding users perceptual orientations. Information & Management 42 (2005) 455-468
5. Chiu C.M., Hsu M.H., Sun S.Y., Lin T.C., and Sun P.C. Usability, quality, value and e-learning continuance decisions. Computers & Education 45 (2005) 399-416
6. Cohen J.B., and Warlop L. A Motivational Perspective on Means-End Chains. In: Reynolds T.J., and Olson J.C. (Eds). Understanding Consumer Decision Making: The Means-End Approach to Marketing and Advertising Strategy, Ch. 17 (2001), Lawrence Erlbaum Associates, Mahwah, New Jersey
7. Dhillon G., and Torkzadeh G. Value-focused assessment of information system security in organizations. Information Systems Journal 16 3 (2006) 293-314
8. Fleiss J.L. Statistical methods for rates and proportions. 2nd ed (1981), John Wiley, New York 38-46
9. Gotthardt M., and Siegert M.J. How to successfully implement e-learning for both students and teachers. Academic Radiology 13 3 (2006) 273-406
10. Govindasamy T. Successful implementation of e-learning pedagogical considerations. Internet and Higher Education 4 (2002) 287-299
11. Grenci R.T. An adaptable customer decision support system for custom configurations. Journal of Computer Information Systems 45 2 (2004) 56-62
12. Grunert K.G., Beckmann S.C., and Sørensen E. Means-End Chains and Laddering: An Inventory of Problems and an Agenda for Research. In: Reynolds T.J., and Olson J.C. (Eds). Understanding Consumer Decision Making: The Means-End Approach to Marketing and Advertising Strategy, Ch. 3 (2001), Lawrence Erlbaum Associates, Mahwah, New Jersey
13. Gutman J. A means-end chain model based on consumer categorization processes. Journal of Marketing 46 (1982) 60-72
14. Hofstede F.T., Audenaert A., Steenkamp J.E.M., and Wedel M. An investigation into the association pattern technique as a qualitative approach to measuring means-end chains. International Journal of Research in Marketing 15 (1998) 37-50
15. Jarratt D., and Fayed R. The impact of market and organisational challenges on marketing strategy decision-making: a qualitative investigation of the business-to-business sector. Journal of Business Research 51 (2001) 61-72
16. Kahle L.R., and Kennedy P. Using the list of values (LOV) to understand consumers. Journal of Consumer Marketing 6 3 (1989) 5-12
17. Koo D.M. The fundamental reasons of e-consumers' loyalty to an online store. Electronic Commerce Research and Applications 5 (2006) 117-130
18. Le Page A., Cox D.N., Russell C.G., and Leppard P.I. Assessing the predictive value of means-end-chain theory: an application to meat product choice by Australian middle-aged women. Appetite 44 (2005) 151-162
19. Lin C.-F., Tsai H.-T., and Fu C.-S. A logic deduction of expanded means-end chains. Journal of Information Science 32 1 (2006) 5-16
20. Low A.L.Y., Low K.L.T., and Koo V.C. Multimedia learning systems: a future interactive educational tool. Internet and Higher Education 6 (2003) 25-40
21. Major N. Modelling teaching strategies. Journal of AI in Education 6 2 (1995) 117-152
22. Malmberg L. Goal-orientation and instructor motivation among instructor applicants and student instructors. Teaching and Teacher Education 22 (2006) 58-76
23. Mishra S. A design framework for online learning environments. British Journal of Educational Technology 33 4 (2002) 493-496
24. Montibeller G., Belton V., Ackermann F., and Ensslin L. Reasoning maps for decision aid: an integrated approach for problem-structuring and multi-criteria evaluation. Journal of Operational Research Society 59 (2008) 575-589
25. Mukhopadhyay M., and Parhar M. Instructional design in multi-channel learning system. British Journal of Educational Technology 32 5 (2001) 543-556
26. Ozdemir Z.D., Altinkemer K., and Barron J.M. Adoption of technology-mediated learning in the U.S. Decision Support Systems 45 (2008) 324-337
27. Olson J.C., and Reynolds F. The Means-End Approach to Understanding Consumer Decision Making. In: Reynolds T.J., and Olson J.C. (Eds). Understanding Consumer Decision Making: The Means-End Approach to Marketing and Advertising Strategy, Ch. 1 (2001), Lawrence Erlbaum Associates, Mahwah, New Jersey
28. Reynolds T.J., and Gutman J. Laddering theory, method, analysis, and interpretation. Journal of Advertising Research 28 (1988) 11-35
29. Reynolds T.J., Dethloff C., and Westberg S. Advancements in Laddering. In: Reynolds T.J., and Olson J.C. (Eds). Understanding Consumer Decision Making: The Means-End Approach to Marketing and Advertising Strategy, Ch. 4 (2001), Lawrence Erlbaum Associates, Mahwah, New Jersey
30. Roca J.C., Chiu C.M., and Martinez F.J. Understanding e-learning continuance intention: an extension of the technology acceptance model. International Journal of Human-Computer Studies 64 (2006) 683-696
31. Rokeach M.J. The Nature of Human Values (1973), Free Press, New York
32. Rosenberg M.J. Cognitive structure and attitudinal affect. Journal of Abnormal and Social Psychology 22 (1956) 368-372
33. Siemer J., and Angelides M.C. A comprehensive method for the evaluation of complete intelligent tutoring systems. Decision Support Systems 22 1 (1998) 85-102
34. Søndergaard H.A. Market-oriented new product development: how can a means-end chain approach affect the process?. European Journal of Innovation Management 8 1 (2005) 79-90
35. Veludo-de-Oliveira T.M., Ikeda A.A., and Campomar M.C. Discussing laddering application by the means-end chain theory. The Qualitative Report 11 4 (2006) 626-642
36. Walker B.A., and Olson J.C. Means-end chains: connecting products with self. Journal of Business Research 22 2 (1991) 111-118
37. Wansink B. Using laddering to understand and leverage a brand's equity. Qualitative Market Research 6 2 (2003) 111
38. Westerman S.J., Tuck G.C., Booth S.A., and Khakzar K. Consumer decision support systems: Internet versus in-store application. Computers in Human Behavior 23 (2007) 2928-2944
39. Xu D., and Wang H. Intelligent agent supported personalization for virtual learning environments. Decision Support Systems 42 (2006) 825-843